arXiv subjects

Manuel Hernández

Publications and source records attributed to Manuel Hernández.

7 recordsLinked to original sources

arXiv2026

A Topos-Theoretic Interpretation of Blockchain Systems: Sheaves of Consensus and the Logic of Decentralized Truth

The predominant formal models for blockchain systems, particularly smart contracts, have largely been drawn from the classical theory of computation, with the finite state machine (FSM) or labeled transition system serving as the primary conceptual tool. However, the FSM relegates the most difficult and novel aspect of a blockchain -- the achievement of consensus in a decentralized environment -- to a complex, often messy, implementation detail that lies outside the formal model itself. But the process of consensus is not an ancillary feature; it is the very essence of the computational phenomenon. To model it faithfully, a new mathematical language is required. The central thesis of this work is that topos theory, the theory of categories of sheaves, provides the native mathematical language for systems defined by local consistency and the construction of global truth.

cs.DC↗

arXiv2026

A Categorial and Sheaf-Theoretic Semantics for Autonomic Component Ensembles

The proliferation of large-scale, decentralized systems of autonomous agents, such as swarms of robots and networked cyber-physical systems, presents a formidable challenge to traditional formal methods. The Software Component Ensemble Language (SCEL) offers a formal model for such systems, but its operational semantics is not ideal for reasoning about global, structural, and emergent properties. This report proposes a new, multi-layered mathematical model for SCEL using category theory and sheaf theory. We argue that a society of robots described in SCEL can be formally modeled as a sheaf on a topological space, where components are points, ensembles are open sets, and distributed knowledge forms the sheaf's data. In this framework, computational processes like information sharing become equivalent to the sheaf-theoretic operation of "gluing" local data. System failures can then be understood and quantified as topological obstructions, measurable by sheaf cohomology. This approach transforms the verification of a complex distributed system into the analysis of the geometry of a mathematical object, providing deep, structural insights for the design of robust autonomic systems.

cs.RO↗

arXiv2026

The Sheaf Laplacian: A Topological Framework for Data Fusion and Consensus in Distributed Sensing Networks

We argue here that traditional network models, which are overwhelmingly based on the mathematical construct of a simple graph, are fundamentally insufficient for capturing the complexity of modern distributed systems. Such systems are characterized by heterogeneous agents with diverse capabilities, high-dimensional and multi-modal data streams, and intricate, context-dependent relationships that cannot be adequately described by a simple connection or a scalar weight. The limitations of these classical models necessitate a new mathematical language, one with far greater expressive power. We have found that sheaf theory provides us with such a language. Moreover, we show that the sheaf Laplacian is a suitable mechanism for data fusion and establishing consensus within distributed sensing networks.

cs.DC↗

arXiv2026

A Sheaf Framework for Strategic Multi-Agent Systems: From Consensus to Nash Equilibria

The coordination of heterogeneous autonomous agents in dynamic, adversarial environments requires simultaneous satisfaction of geometric constraints, logical consistency, temporal reasoning, and strategic optimization. Existing sheaf- and topos-theoretic frameworks provide powerful tools for geometric consensus, knowledge alignment, and causal planning, but lack explicit models for value, reward, and strategic choice. This report presents a unified categorical framework that integrates event calculus, SCEL-like ensemble formation, and game-theoretic reward structures into a single Grothendieck topos of time-space histories. We introduce the notion of a \emph{game sheaf} whose stalks contain utility functions and policy distributions, and restriction maps encode both parallel transport and best-response dynamics. We prove that Nash equilibria correspond to global sections of a derived best-response correspondence sheaf, while cohomological obstructions classify failures of strategic consistency. A detailed case study of an immunological ``bastion defense'' scenario -- heterogeneous agents forming attack/defense ensembles under resource constraints -- demonstrates the framework's expressiveness. This synthesis provides a rigorous foundation for verifiable, autonomic, and economically rational multi-agent systems.

cs.GT↗

arXiv2026

The Cartan-Topos Protocol: A Unified Geometric and Categorical Framework for Resilient Multi-Agent Coordination

Multi-agent coordination faces a fundamental divide between continuous Euclidean consensus, which fails under non-integrable constraints, and discrete symbolic logic, which collapses under open-world assumptions. This report presents a unified geometric and categorical framework bridging these paradigms. Agent states are modeled on homogeneous manifolds (Lie groups, Grassmannians) with consensus achieved via Riemannian center-of-mass flows. Clifford-algebraic representations (rotors, motors) enable singularity-free SE(3) pose synchronization. Network interactions are formalized as cellular sheaves, where heterogeneous stalks connected by linear restriction maps replace uniform weights; the sheaf Laplacian drives diffusion toward globally consistent sections. The Cartan connection encodes logical holonomy directly into restriction maps. Asynchronous nonlinear sheaf diffusion guarantees linear convergence to Dirichlet energy minimizers under bounded delays. Sheaf-Theoretic Planning (STP) models time as a Grothendieck topos, using intuitionistic logic and abductive repair for resilient temporal reasoning. Applications include discourse sheaves for opinion dynamics and knowledge sheaves for graph embedding. This synthesis establishes geometric consensus as a universal foundation for resilient multi-agent systems across physical, epistemic, and temporal domains.

cs.DC↗

arXiv2026

Sheaf-Theoretic Planning: A Categorical Foundation for Resilient Multi-Agent Autonomous Systems

The challenge of engineering autonomous agents capable of navigating the stochastic and adversarial nature of the physical world has historically resided at the intersection of symbolic logic and control theory. Traditional multi-agent system (MAS) frameworks have relied heavily on monolithic logical models -- primarily variations of the event calculus and situation calculus -- to represent action, change, and temporal persistence. While these classical systems provide robust solutions to the frame problem through mechanisms like circumscription and successor state axioms, they are inherently limited by a closed-world assumption that fails in the face of unobserved agent interventions, plan interruptions, and divergent belief-reality states. The paradigm of Sheaf-Theoretic Planning (STP) emerges as a transformative alternative, grounding the problem of multi-agent coordination under the mathematical structures of topos theory and sheaf semantics. This report provides an exhaustive analysis, justification, and extension of the STP framework, exploring its categorical foundations, implementation feasibility, and role in the future of resilient autonomous systems.

cs.AI↗

arXiv2018

Deriving sorting algorithms via abductive logic program transformation

Logic program transformation by the unfold/fold method ad- vocates the writing of correct logic programs via the application of some rules to a naive program. This work focuses on how to overcome subgoal- introduction difficulties in synthesizing efficient sorting algorithms from an naive sorting algorithm, through logic program transformation and abductive reasoning.

cs.PL↗